Temperature measurement method, device, and computer equipment

Abstract

The present application provides a temperature measurement method, device, and computer equipment, which relate to the field of temperature measurement technology and are used to improve the accuracy of temperature measurement. The method mainly includes: obtaining the measured temperature value of the user at the current moment; if the measured temperature value at the current moment is greater than the first threshold, then according to the measured temperature value at the current moment and the measured temperature value of the user at the previous moment, as well as the amplification factor and the adjustment factor, the predicted temperature value at the current moment is calculated; the adjustment factor is a constant factor, and the amplification factor is the amplification factor of the temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user; the predicted temperature value at the current moment is used as the body temperature of the user.

Description

Technical Field

[0001] The present application relates to the field of temperature measurement technology, and in particular to a temperature measurement method, device, computer equipment and storage medium. Background Art

[0002] Predictive electronic thermometers generally produce results in tens of seconds to 2 minutes. This predictive thermometer uses a prediction algorithm for any person and any measurement situation. However, due to individual differences in the subjects, such as different subcutaneous fat thickness and different grasp of the monitoring position when using the thermometer, there may be a large difference between the predicted value and the actual measured value when measuring for some people. Therefore, how to improve the accuracy of temperature measurement has become an urgent problem to be solved. Summary of the invention

[0003] Embodiments of the present application provide a temperature measurement method, apparatus, computer equipment, and storage medium for improving the accuracy of temperature measurement.

[0004] An embodiment of the present invention provides a temperature measurement method, the method comprising:

[0005] Get the user's measured temperature value at the current moment;

[0006] If the measured temperature value at the current moment is greater than the first threshold, the predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value at the previous moment of the user as well as the amplification factor and the adjustment factor; the adjustment factor is a constant factor, and the amplification factor is the amplification factor of the temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user;

[0007] The predicted temperature value at the current moment is used as the body temperature of the user.

[0008] An embodiment of the present invention provides a temperature measurement device, the device comprising:

[0009] The acquisition module is used to obtain the user's measured temperature value at the current moment;

[0010] A calculation module, configured to calculate, if the measured temperature value at the current moment is greater than a first threshold, a predicted temperature value at the current moment according to the measured temperature value at the current moment and the measured temperature value at the previous moment of the user, as well as an amplification factor and an adjustment factor; the adjustment factor is a constant factor, and the amplification factor is an amplification factor of a temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user;

[0011] A determination module is used to use the predicted temperature value at the current moment as the body temperature of the user.

[0012] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the temperature measurement method is implemented when the processor executes the computer program.

[0013] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the temperature measurement method is implemented.

[0014] The present invention provides a temperature measurement method, device, computer equipment and storage medium. First, the measured temperature value of the user at the current moment is obtained; if the measured temperature value at the current moment is greater than a first threshold value, the predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value of the user at the previous moment, as well as an amplification factor and an adjustment factor; finally, the predicted temperature value at the current moment is used as the body temperature of the user. Among them, the adjustment coefficient is a constant coefficient, and the amplification factor is the amplification factor of the temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user. The present invention calculates the predicted temperature value according to the data corresponding to each user, that is, the predicted temperature value is calculated according to the measured temperature value at the current moment and the measured temperature value at the previous moment of each user, as well as the amplification factor and the adjustment factor, so that the predicted temperature value is more targeted, thereby improving the accuracy of temperature measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of a temperature measurement method provided in this application;

[0016] Figure 2 The screen interface display diagram of the electronic thermometer provided for this application;

[0017] Figure 3 A trend graph of temperature changes when a user measures body temperature provided by this application;

[0018] Figure 4 Another temperature measurement method flow chart provided for this application;

[0019] Figure 5 A schematic diagram of the structure of the temperature measurement device provided in this application;

[0020] Figure 6 Schematic diagram of the computer equipment provided for this application. DETAILED DESCRIPTION

[0021] In order to better understand the above-mentioned technical scheme, the technical scheme of the embodiments of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical scheme of the embodiments of the present application, rather than limitations on the technical scheme of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments may be combined with each other.

[0022] See also Figure 1 , a temperature measurement method provided by an embodiment of the present invention is applied to a temperature measurement device, such as an electronic thermometer, etc. The method specifically includes steps S101 to S103:

[0023] Step S101, obtaining the temperature value measured by the user at the current moment.

[0024] Specifically, this embodiment can use an electronic thermometer to measure the user's measured temperature value at the current moment, that is, place the temperature measuring part of the electronic thermometer under the armpit, forehead, wrist or mouth of the user (the object being measured), and then obtain the measured temperature value at the current moment.

[0025] In this embodiment, before measuring the temperature, the user may also enter the user's identification information, which is used to uniquely identify the user. Then, when obtaining the temperature value measured by the user at the current moment, the user's identification information is obtained, so as to determine the temperature value measured by the user at the last moment according to the user's identification information.

[0026] like Figure 2 The screen interface of the electronic thermometer shown in the figure, the P on the screen interface is the abbreviation of person, which can be followed by any number from 0 to n to represent different people. For example, P1 on the screen interface represents user No. 1, and the user can choose one from P0 to Pn to represent himself, and n is a natural number.

[0027] According to Figure 3 The trend curve of temperature change when the user measures the body temperature shown in the figure shows that in the initial stage of the body temperature measurement, the temperature rises quickly (the stage of rapid temperature change), and after a period of temperature measurement, the temperature of the thermometer tends to change slowly (the stage of slow temperature change) because the thermometer and the human skin are close to reaching thermal equilibrium, and it takes a long time (such as 5-10 minutes) for the user's body temperature to reach a stable state. Based on this characteristic of body temperature measurement, this embodiment will start the fast temperature measurement algorithm in the stage of rapid temperature change, that is, obtain the measured temperature value of the user at the current moment through step S101, and then calculate the temperature of the human skin when the temperature equilibrium is reached before the temperature equilibrium is reached based on the measured temperature value measured in this stage, that is, predict the user's body temperature before the temperature equilibrium is reached, so as to improve the efficiency of temperature measurement.

[0028] It should be noted that due to the influence of various factors during the rapid temperature change stage, there may be situations where the measured temperature value is unstable, which may cause errors in the calculation results. For example, if the user uses the thermometer with the wrong posture, or the thermometer is placed in the wrong position, etc., it will affect the actual temperature measurement results during the rapid temperature change stage. In order to reduce the impact of the starting temperature on the calculated value, this embodiment starts the prediction of the temperature value by setting a first threshold, that is, when the measured temperature value at the current moment is greater than the first threshold, step S102 is executed to calculate the predicted temperature value at the current moment.

[0029] Furthermore, the present embodiment can obtain the measured temperature value at the current moment according to a preset time interval, and the preset time interval can be 1 second, 2 seconds, or 3 seconds, etc., which is not specifically limited in the present embodiment. If the preset time interval is 2 seconds and the current time is 10:00:00, the user's body temperature value is obtained for the first time at 10:00:02 (i.e., the electronic thermometer stays at a certain position of the user for 2 seconds), and then it is determined whether the user's body temperature value obtained for the first time is greater than the first threshold value, and if it is greater, it jumps to step S102 to continue execution; if it is less than or equal to, the user's body temperature value is obtained for the second time at 10:00:04 (i.e., the electronic thermometer stays at a certain position of the user for 4 seconds), and then it is determined again whether the measured temperature value obtained for the second time is greater than the first threshold value, and so on until the measured temperature value at the current moment is greater than the first threshold value, and step S102 is executed.

[0030] Step S102: If the measured temperature value at the current moment is greater than the first threshold, a predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value of the user at the previous moment as well as an amplification factor and an adjustment factor.

[0031] The adjustment coefficient is a constant coefficient, and the amplification coefficient is an amplification coefficient of the temperature difference between the measured temperature value at the current moment and the measured temperature value of the user at the previous moment. The first threshold can be determined according to the amplification coefficient and the adjustment coefficient.

[0032] In an optional embodiment provided by the present invention, the step of calculating the predicted temperature value at the current moment according to the measured temperature value at the current moment, the measured temperature value at the previous moment of the user, the amplification factor and the adjustment factor includes:

[0033] By formula T P =T n +(T n -T n-△t )*A+C to calculate the predicted temperature value at the current moment;

[0034] Among them, the T P is the predicted temperature value, the Tn is the measured temperature value at the current moment, that is, the measured temperature value obtained in step S101, wherein T n-△t is the temperature value measured by the user at the last moment, A is the amplification factor, C is the adjustment factor, and Δt is the time interval. The time interval can be 1 second, 2 seconds, or 3 seconds, etc., which is not specifically limited in this embodiment. For example, if the current time is 10:00:02 and Δt is 2 seconds, then the last time is 10:00:00.

[0035] It should be noted that the moment interval △t in this embodiment can be the same as the preset time interval in step S102, such as 2 seconds or 3 seconds; it can also be different from the preset time interval in step S102. Preferably, in order to further improve the efficiency of calculating the predicted temperature value at the current moment, the moment interval △t in this implementation is smaller than the preset time interval, such as when the preset time interval is 2 seconds, the moment interval △t is 1 second.

[0036] Step S103: taking the predicted temperature value at the current moment as the body temperature of the user.

[0037] Specifically, after obtaining the user's body temperature, the user's body temperature can be output on the screen of the electronic thermometer, or the user's body temperature can be input through voice broadcast, which is not specifically limited in this embodiment. It should be noted that after obtaining the user's body temperature, it can also be determined whether the user's body temperature is not in a normal temperature range. If it is not in the normal temperature range, an alarm message is output to prompt the user of abnormal body temperature.

[0038] A temperature measurement method provided by an embodiment of the present invention first obtains the measured temperature value of the user at the current moment; if the measured temperature value at the current moment is greater than a first threshold value, the predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value of the user at the previous moment, as well as the amplification factor and the adjustment factor; finally, the predicted temperature value at the current moment is used as the body temperature of the user. Among them, the adjustment coefficient is a constant coefficient, and the amplification factor is the amplification factor of the temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user. The present invention calculates the predicted temperature value according to the data corresponding to each user, that is, the predicted temperature value is calculated according to the measured temperature value at the current moment and the measured temperature value at the previous moment of each user, as well as the amplification factor and the adjustment factor, so that the predicted temperature value is more targeted, thereby improving the accuracy of temperature measurement.

[0039] See also Figure 4 , a temperature measurement method provided by an embodiment of the present invention is applied to a temperature measurement device, such as an electronic thermometer, etc. The method specifically includes steps S201 to S207:

[0040] Step S201, obtaining the temperature value measured by the user at the current moment.

[0041] Step S202: If the measured temperature value at the current moment is greater than the first threshold, a predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value of the user at the previous moment as well as an amplification factor and an adjustment factor.

[0042] Among them, step S201 and step S202 are Figure 1 The description of the corresponding steps in is the same as that in the embodiment, and will not be repeated here.

[0043] Step S203, determining whether the difference between the predicted temperature value at the current moment and the predicted temperature value at the previous moment is less than a second threshold.

[0044] In this embodiment, after the predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value at the previous moment of the user, as well as the amplification factor and the adjustment factor, it is necessary to determine whether the difference between the predicted temperature value at the current moment and the predicted temperature value at the previous moment is less than the second threshold value. If it is less than the second threshold value, the predicted temperature value of the user tends to be stable, and the predicted temperature value at the current moment can be used as the body temperature of the user; if it is greater than or equal to the second threshold value, the step of jumping to step S201 to obtain the measured temperature value of the user at the current moment is continued until the difference between the predicted temperature value at the current moment and the predicted temperature value at the previous moment is less than the second threshold value. The second threshold value can be determined based on the amplification factor and the adjustment factor.

[0045] Specifically, this embodiment calculates the predicted temperature value at the current moment according to the time interval Δt (such as 1 second, 2 seconds, etc.) until the difference between the predicted temperature value at the current moment and the predicted temperature value at the previous moment is less than the second threshold. For example, the current time is 10:00:00, and the time interval △t is 2 seconds. The predicted temperature value corresponding to the time 10:00:00 (the predicted temperature value calculated for the first time) is calculated based on the actual temperature measurement values ​​corresponding to the time 10:00:00 and the time 09:59:58, and then the predicted temperature value corresponding to the time 10:00:02 (the predicted temperature value calculated for the second time) is calculated based on the actual temperature measurement values ​​corresponding to the time 10:00:02 and the time 10:00:00, and it is calculated whether the difference between the predicted temperature value calculated for the second time and the predicted temperature value calculated for the first time is less than the second threshold value. If it is less than the second threshold value, the predicted temperature value calculated for the second time is used as the user's body temperature and is output; if it is greater than or equal to the second threshold value, the predicted temperature value needs to be calculated for the third time until the difference between the predicted temperature value calculated currently (current time) and the predicted temperature value calculated last time (last time) is less than the second threshold value.

[0046] In this embodiment, the formula T P =T n +(T n -T n-△t )*A+C to calculate the predicted temperature value at the current moment; the T P is the predicted temperature value, the T n is the measured temperature value at the current moment, that is, the measured temperature value obtained in step S101, wherein T n-△t is the temperature value measured by the user at the last moment, A is the amplification factor, C is the adjustment factor, and Δt is the time interval.

[0047] It should be noted that, before calculating the predicted temperature value at the current moment through the above formula, this embodiment needs to determine the amplification factor and the adjustment factor through the following paradigm: obtain sample data, the sample data including the predicted temperature value and the actual temperature value; perform linear fitting on the sample data to obtain a fitting model, and determine the constant parameters in the fitting model as the amplification factor and the adjustment factor.

[0048] It should be noted that the sample data in this embodiment can be obtained by collecting temperature data of a large number of users. That is, when performing linear fitting, there is no need to classify the source of the sample data. The fitting model is obtained by fitting all the sample data, and then the constant parameters in the fitting model are determined as the amplification factor and the adjustment factor.

[0049] Preferably, the present embodiment can screen the sample data according to different conditions, and then fit the screened sample data to obtain a fitting model. Specifically, the present embodiment can screen by age, gender, identity attributes and other conditions, which are not specifically limited in the present embodiment.

[0050] For example, sample data with the identity attribute of pregnant women can be screened, and then a fitting model can be obtained by fitting based on the screened sample data. The constant parameters in the fitting model are determined as the amplification factor and the adjustment factor, and the amplification factor and the adjustment factor are written into the electronic thermometer, so that when a user with the identity attribute of a pregnant woman measures the temperature, she can enter her identity attribute and calculate the predicted temperature value according to the amplification factor and the adjustment factor corresponding to the identity attribute, thereby making the predicted temperature value more targeted and improving the accuracy of the predicted temperature value.

[0051] Furthermore, after obtaining the amplification coefficient and the adjustment coefficient by fitting the model, this embodiment calculates the first threshold and the second threshold according to the amplification coefficient and the adjustment coefficient.

[0052] Specifically, through the formula T start =bC / A calculate the first threshold; T startis the first threshold.

[0053] Wherein, b is a constant, A is the amplification coefficient, and C is the adjustment coefficient. Preferably, b=2.

[0054] Specifically, through the formula T end =C / dA calculates the second threshold; T end is the second threshold.

[0055] Wherein, d is a constant, A is the amplification coefficient, and C is the adjustment coefficient. Preferably, d=3.5.

[0056] Step S204: If the temperature is less than the second threshold, the predicted temperature value at the current moment is used as the body temperature of the user.

[0057] In this embodiment, if the difference between the predicted temperature value at the current moment and the predicted temperature value at the previous moment is less than the second threshold, the predicted temperature value at the current moment is used as the body temperature of the user. The rapid temperature measurement mode is terminated, and the user's body temperature is output. For example, a beeping sound prompts the user that the rapid temperature measurement mode has ended, and the user is prompted to view the rapid temperature measurement result on the display screen of the thermometer.

[0058] Another temperature measurement method provided by an embodiment of the present invention first obtains the measured temperature value of the user at the current moment; if the measured temperature value at the current moment is greater than the first threshold, the predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value of the user at the previous moment, as well as the amplification factor and the adjustment factor; finally, the predicted temperature value at the current moment is used as the body temperature of the user. Among them, the adjustment coefficient is a constant coefficient, and the amplification factor is the amplification factor of the temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user. The present invention calculates the predicted temperature value according to the data corresponding to each user, that is, the predicted temperature value is calculated according to the measured temperature value at the current moment and the measured temperature value at the previous moment of each user, as well as the amplification factor and the adjustment factor, so that the predicted temperature value is more targeted, thereby improving the accuracy of temperature measurement.

[0059] Furthermore, after taking the predicted temperature value at the current moment as the body temperature of the user, the method further includes:

[0060] Step S205, calculating the absolute value of the temperature difference between the user's body temperature and the user's actual temperature.

[0061] In an embodiment of the present invention, after the user's body temperature (predicted temperature value) is calculated, the user can continue to use the thermometer to measure the temperature. At this time, the thermometer enters the normal temperature measurement mode, and the thermometer will not display the predicted temperature value, but will display the temperature value actually measured by the thermometer. After obtaining the user's actual temperature, the absolute value of the temperature difference between the user's temperature and the user's actual temperature can also be calculated, so as to determine whether it is necessary to continue fitting the fitting model based on the absolute value of the temperature difference, that is, whether it is necessary to update the amplification factor and the adjustment factor.

[0062] For example, when the absolute value of the temperature difference between the user's body temperature and the user's actual temperature is greater than 0.2 degrees, execute step S206; if it is less than or equal to 0.2 degrees, it means that the accuracy of the user's body temperature calculated according to the current amplification factor and adjustment factor meets the requirements, and there is no need to update the amplification factor and adjustment factor.

[0063] Step S206, determining the interval range corresponding to the absolute value of the temperature difference.

[0064] In this embodiment, the temperature is divided into a plurality of intervals, and the fitting model needs to be refitted for a certain number of user temperature data in different intervals.

[0065] For example, the temperature is divided into four intervals: 0.2 to 0.3 degrees, 0.3 to 0.4 degrees, 0.4 to 0.5 degrees, and above 0.5 degrees.

[0066] Step S207, obtaining the body temperatures of a number of users corresponding to the interval range and the actual temperatures of the users.

[0067] In this embodiment, the fitting model is refitted according to the body temperature of the corresponding number of users and the actual temperature of the users required for different interval ranges. For example, 0.3-0.4 requires more than N sets of data, while the gap between 0.2-0.3 requires more than 3N sets of data; the gap between 0.1-0.2 requires more than 10N sets of data. As the gap decreases, more data may be needed to refit the fitting model to avoid the impact of the errors of the amplification coefficient and the adjustment coefficient.

[0068] It should be noted that after determining the interval range corresponding to the absolute value of the temperature difference, this embodiment can output temperature entry prompt information to prompt the user to measure the user temperature and the user's actual temperature a specific number of times, and the specific number of times is the number corresponding to the interval range.

[0069] Step S208: refit the fitting model according to the acquired body temperature of the user and the actual temperature of the user, and update the amplification factor and the adjustment factor according to the constant parameters in the fitting result.

[0070] In this embodiment, the body temperatures of a number of users corresponding to the interval range and the actual temperatures of the users can be obtained based on the user's identity identification or the user's identity attributes, and then the fitting model is refitted based on the obtained body temperatures of the users and the actual temperatures of the users, and the amplification coefficient and the adjustment coefficient are updated according to the constant parameters in the fitting results.

[0071] For example, for user A, the fitting model can be refitted based on the body temperature and actual temperature of user A, and the amplification factor and the adjustment factor can be updated according to the constant parameters in the fitting results; for another example, for the body temperature and actual temperature of an elderly person in the family with an identity attribute of over 60 years old, the fitting model can be refitted, and the amplification factor and the adjustment factor can be updated according to the constant parameters in the fitting results.

[0072] In addition, this embodiment can also obtain the user's body temperature and the user's actual temperature according to a certain time period, and calculate the absolute value of the temperature difference between the user's body temperature and the user's actual temperature, and then based on the average value of the absolute value of the temperature difference within the period, if the average value is greater than a certain value, it is necessary to re-fit the fitting model according to the user's body temperature within the period and the user's actual temperature, and update the amplification factor and the adjustment factor according to the constant parameter in the fitting result; if the average value is less than or equal to the value, there is no need to adjust the amplification factor and the adjustment factor.

[0073] In this embodiment, the updated amplification factor and adjustment factor are associated and stored with the corresponding user's identity identification or identity attribute in the electronic thermometer, and the next time the relevant user measures body temperature, the adjusted updated amplification factor and adjustment factor will be used for rapid temperature measurement.

[0074] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0075] In one embodiment, a temperature measurement device is provided, which corresponds one-to-one to the temperature measurement method in the above embodiment. Figure 5 As shown, the functional modules of the temperature measurement device are described in detail as follows:

[0076] The acquisition module 51 is used to obtain the temperature value measured by the user at the current moment;

[0077] A calculation module 52, configured to calculate, if the measured temperature value at the current moment is greater than a first threshold, a predicted temperature value at the current moment according to the measured temperature value at the current moment and the measured temperature value at the previous moment of the user, as well as an amplification factor and an adjustment factor; the adjustment factor is a constant factor, and the amplification factor is an amplification factor of a temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user;

[0078] The determination module 53 is used to use the predicted temperature value at the current moment as the body temperature of the user.

[0079] In an optional embodiment, the determination module 53 is specifically configured to:

[0080] Determine whether the difference between the predicted temperature value at the current moment and the predicted temperature value at the previous moment is less than a second threshold;

[0081] If it is less than a second threshold, the predicted temperature value at the current moment is used as the body temperature of the user;

[0082] If it is greater than or equal to the second threshold, the process jumps to the step of obtaining the temperature value measured by the user at the current moment and continues to execute.

[0083] In an optional embodiment, the calculation module 52 is specifically configured to:

[0084] By formula T P =T n +(T n -T n-△t )*A+C to calculate the predicted temperature value at the current moment;

[0085] Among them, the T P is the predicted temperature value, the T n is the measured temperature value at the current moment, the T n-△t is the temperature value measured by the user at the last moment, A is the amplification factor, C is the adjustment factor, and Δt is the time interval.

[0086] In an optional embodiment, the acquisition module 51 is further used to acquire sample data, wherein the sample data includes a predicted temperature value and an actual temperature value;

[0087] The determination module 53 is further used to perform linear fitting on the sample data to obtain a fitting model, and determine the constant parameters in the fitting model as the amplification factor and the adjustment factor.

[0088] In an optional embodiment, the calculation module 52 is specifically configured to:

[0089] By formula T start=bC / A calculates the first threshold;

[0090] Wherein, b is a constant, A is the amplification coefficient, and C is the adjustment coefficient.

[0091] In an optional embodiment, the calculation module 52 is specifically configured to:

[0092] By formula T end =C / dA calculates the second threshold;

[0093] Wherein, d is a constant, A is the amplification coefficient, and C is the adjustment coefficient.

[0094] In an optional embodiment, the calculation module 52 is further used to calculate the absolute value of the temperature difference between the user's body temperature and the user's actual temperature;

[0095] A calculation module 52, used to determine the interval range corresponding to the absolute value of the temperature difference;

[0096] An acquisition module 51 is used to acquire the body temperatures of the users corresponding to the interval range and the actual temperatures of the users;

[0097] The determination module 53 is used to refit the fitting model according to the acquired body temperature of the user and the actual temperature of the user, and update the amplification factor and the adjustment factor according to the constant parameters in the fitting result.

[0098] For the specific definition of the temperature measuring device, please refer to the definition of the temperature measuring method above, which will not be repeated here. Each module in the above-mentioned device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0099] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a temperature measurement method is implemented.

[0100] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0101] Get the user's measured temperature value at the current moment;

[0102] If the measured temperature value at the current moment is greater than the first threshold, the predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value at the previous moment of the user as well as the amplification factor and the adjustment factor; the adjustment factor is a constant factor, and the amplification factor is the amplification factor of the temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user;

[0103] The predicted temperature value at the current moment is used as the body temperature of the user.

[0104] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0105] Get the user's measured temperature value at the current moment;

[0106] If the measured temperature value at the current moment is greater than the first threshold, the predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value at the previous moment of the user as well as the amplification factor and the adjustment factor; the adjustment factor is a constant factor, and the amplification factor is the amplification factor of the temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user;

[0107] The predicted temperature value at the current moment is used as the body temperature of the user.

[0108] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0109] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0110] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A temperature measurement method, characterized in that: The method comprises: Get the user's measured temperature value at the current moment; If the measured temperature value at the current moment is greater than the first threshold, the predicted temperature value at the current moment is calculated based on the measured temperature value at the current moment and the measured temperature value at the previous moment of the user as well as the amplification factor and the adjustment factor; the adjustment factor is a constant factor, and the amplification factor is the amplification factor of the temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user; Using the predicted temperature value at the current moment as the body temperature of the user; The step of calculating the predicted temperature value at the current moment according to the measured temperature value at the current moment, the measured temperature value at the previous moment of the user, the amplification factor and the adjustment factor comprises: By formula Calculate and obtain the predicted temperature value at the current moment; Among them, the T p is the predicted temperature value, the T n is the measured temperature value at the current moment, the T n-Δt is the temperature value measured by the user at the last moment, A is the amplification factor, C is the adjustment factor, and Δt is the time interval; By formula T start =bC / A calculate the first threshold; T start is the first threshold; Wherein, b is a constant, A is the amplification coefficient, and C is the adjustment coefficient.

2. The method according to claim 1, characterized in that The using the predicted temperature value at the current moment as the body temperature of the user includes: Determine whether the difference between the predicted temperature value at the current moment and the predicted temperature value at the previous moment is less than a second threshold; If it is less than a second threshold, the predicted temperature value at the current moment is used as the body temperature of the user; If it is greater than or equal to the second threshold, the process jumps to the step of obtaining the temperature value measured by the user at the current moment and continues to execute.

3. The method according to claim 1, characterized in that The method further comprises: Acquire sample data, wherein the sample data includes a predicted temperature value and an actual temperature value; A fitting model is obtained by performing linear fitting on the sample data, and constant parameters in the fitting model are determined as the amplification coefficient and the adjustment coefficient.

4. The method according to claim 2, characterized in that: The method further comprises: By formula T end =C / dA calculates the second threshold; T end is the second threshold; Wherein, d is a constant, A is the amplification coefficient, and C is the adjustment coefficient.

5. The method according to claim 3, characterized in that: After taking the predicted temperature value at the current moment as the body temperature of the user, the method further includes: Calculating an absolute value of a temperature difference between the user's body temperature and the user's actual temperature; Determine the interval range corresponding to the absolute value of the temperature difference; Acquire the body temperatures of the number of users corresponding to the interval range and the actual temperatures of the users; The fitting model is refitted according to the acquired body temperature of the user and the actual temperature of the user, and the amplification factor and the adjustment factor are updated according to the constant parameters in the fitting result.

6. A temperature measuring device, characterized in that: The device comprises: The acquisition module is used to obtain the user's measured temperature value at the current moment; A calculation module, configured to calculate, if the measured temperature value at the current moment is greater than a first threshold, a predicted temperature value at the current moment according to the measured temperature value at the current moment and the measured temperature value at the previous moment of the user, as well as an amplification factor and an adjustment factor; the adjustment factor is a constant factor, and the amplification factor is an amplification factor of a temperature difference between the measured temperature value at the current moment and the measured temperature value at the previous moment of the user; a determination module, configured to use the predicted temperature value at the current moment as the body temperature of the user; The calculation module is also used to calculate Calculate and obtain the predicted temperature value at the current moment; Among them, the T p is the predicted temperature value, the T n is the measured temperature value at the current moment, the T n-Δt is the temperature value measured by the user at the last moment, A is the amplification factor, C is the adjustment factor, and Δt is the time interval; The calculation module is also used to calculate the start =bC / A calculate the first threshold; T start is the first threshold; Wherein, b is a constant, A is the amplification coefficient, and C is the adjustment coefficient.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the temperature measurement method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the temperature measurement method according to any one of claims 1 to 5 is implemented.

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